baecun — CS2 Stats

76561198147984331[U:1:187718603]Steam profile ↗✓ No bans

2,273Tracked matches34%Win rate2023Tracked since

CSDB Rating5.0 DevelopingPassive Rifler

Premier CS Rating16,603Purple band · top ~22% of ranked players (population est.)

CSDB Leaderboard#20796 of 37280 tracked

FaceitLevel 6 · 1,271 ELOTop 54.0% of ranked FACEIT players

WingmanMaster Guardian II

Ladder ranks via Leetify

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Performance scores

Aim72

Positioning39

Utility53

0–100 skill scores via Leetify.

Recent form

COLD47–50–3Last 10047%Win rateLLLLLLWWLL

Last 10 vs previous 10: -10pp win rate · +0.01 avg rating

Player DNA

Primary style: Passive Rifler — Aim-led profile without a single dominant tendency.

Aim7.2

Aggression1.9

Utility5.3

Positioning3.9

Opening Duels0.0

Clutch3.0

Limited utility dependence

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

Your pro match

Plays most like NiKo 76% playstyle similarity

Most alike: utility contribution, aim profile.

Where you differ: lower opening-duel success; lower opening-fight frequency.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

Strengths & areas to improve

Areas to improve

Positioning. Positioning trails aim by 32 points — deaths here waste a strong aim profile.

Reaction time. 647ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Generated by fixed rules over this profile's own numbers — no model, no guessing; silent when the sample is too small to support a claim.

CSDB Rating breakdown

Aim7.2

Positioning3.9

Utility5.3

Mechanics8.2

Opening Duels0.0

Win Impact0.0

Composite 5.0/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01−0.01

first ⅓ avg 0.01 → last ⅓ avg -0.01

Reaction time654ms−11ms

first ⅓ avg 665ms → last ⅓ avg 654ms

Headshot accuracy14.9%−2.6%

first ⅓ avg 17.4% → last ⅓ avg 14.9%

Rolling 5-match average across the last 100 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Highlights

0.14Best rating — inferno 9–4

13–2Biggest win — ancient

5Longest win streak

L6Current streak

13–10In matches decided by ≤2 rounds

9Overtime games

Map breakdown

ancientBest map · 67% over 21infernoWeakest map · 29% over 7

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	23	11–12	48%	-0.01
ancient	S	21	14–7	67%	0.01
nuke	C	18	8–10	44%	0.01
mirage	C	11	4–7	36%	0.03
cache	C	10	4–6	40%	-0.01
inferno	D	7	2–5	29%	0.00
anubis	D	6	2–4	33%	0.02
overpass	—	3	1–2	33%	0.01
vertigo	—	1	1–0	100%	-0.07

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (29% over 7). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

172Matches

52%Win rate

1.06Avg K/D

77.3ADR

37%Headshot %

Clutches & streaks

35%1v1 clutch win

18%1v2 clutch win

7Longest win streak

Recent Faceit resultsWLLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	38	45%	1.01	15.1
Dust2	33	52%	1.10	16.3
Inferno	27	37%	0.94	14.6
Nuke	27	67%	1.25	17.9
Anubis	20	65%	1.05	14.3
Ancient	17	47%	0.94	14.8
Train	6	67%	1.00	15.5
Overpass	3	67%	1.46	17.0

Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

14.1%Headshot accuracy

37.3%Accuracy (enemy spotted)

38.1%Spray accuracy

86.9%Counter-strafing

9.0°Preaim

647msReaction time

26.6%T opening success

29.8%CT opening success

0.63Enemies flashed / flash

8.7%Flash assists

13.38HE damage / grenade

4.45Flashes / match

Recommended for you

Chosen by comparing your tracked metrics against the thresholds we flag — the measurement behind each one is shown, so you can disagree with it.

Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 14.0754% — below the 15% mark we flag
Aim Training →
Advanced Mechanics
You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.
T opening duels 26.5991% — below the 40% mark we flag

Spend your practice time on Inferno

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

29% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
dust2	6–13	-0.03	22%	23 Aug →
ancient	9–13	0.01	15%	23 Aug →
dust2	11–13	-0.01	10%	20 Aug →
dust2	10–13	-0.03	12%	15 Aug →
nuke	11–13	0.06	21%	14 Aug →
cache	7–11	-0.05	14%	13 Aug →
vertigo	9–3	-0.07	18%	5 Aug →
overpass	9–3	0.04	21%	4 Aug →
cache	5–13	0.00	27%	31 Jul →
mirage	14–16	0.07	16%	30 Jul →
dust2	13–10	0.07	15%	30 Jul →
dust2	4–13	-0.09	13%	29 Jul →
nuke	8–13	-0.04	12%	26 Jul →
ancient	8–13	-0.07	8%	24 Jul →
ancient	8–13	-0.01	12%	24 Jul →
nuke	13–11	0.08	15%	23 Jul →
cache	11–7	-0.03	6%	23 Jul →
ancient	12–12	0.04	17%	19 Jul →
nuke	3–13	-0.09	14%	19 Jul →
dust2	9–13	-0.01	19%	18 Jul →
dust2	13–9	-0.05	10%	18 Jul →
nuke	9–13	-0.02	11%	16 Jul →
cache	11–13	0.04	13%	14 Jul →
mirage	4–2	0.12	14%	14 Jul →
ancient	13–2	-0.03	19%	13 Jul →
ancient	13–11	-0.00	11%	12 Jul →
inferno	9–13	-0.03	13%	12 Jul →
dust2	13–9	-0.04	8%	12 Jul →
anubis	9–13	0.01	13%	12 Jul →
mirage	13–16	-0.04	14%	11 Jul →
ancient	13–11	-0.03	17%	11 Jul →
dust2	13–11	0.01	12%	11 Jul →
dust2	13–8	0.02	27%	11 Jul →
ancient	13–4	-0.06	12%	11 Jul →
cache	9–13	-0.00	17%	11 Jul →
dust2	13–10	-0.01	12%	11 Jul →
anubis	9–13	-0.01	4%	10 Jul →
cache	15–15	0.06	11%	10 Jul →
cache	13–6	0.01	8%	10 Jul →
nuke	13–5	0.07	10%	10 Jul →
mirage	13–5	0.07	12%	10 Jul →
cache	1–13	-0.16	0%	8 Jul →
ancient	11–13	0.01	11%	5 Jul →
nuke	14–16	0.01	18%	5 Jul →
ancient	13–4	0.02	13%	5 Jul →
overpass	11–13	-0.02	15%	4 Jul →
nuke	11–13	0.03	10%	4 Jul →
dust2	8–13	-0.01	9%	4 Jul →
mirage	9–13	0.04	14%	4 Jul →
inferno	9–4	0.14	43%	3 Jul →
ancient	13–11	-0.02	8%	3 Jul →
nuke	13–11	0.04	20%	3 Jul →
cache	13–10	0.05	19%	3 Jul →
inferno	6–9	0.06	30%	3 Jul →
ancient	6–13	-0.01	17%	1 Jul →
nuke	13–3	0.06	11%	1 Jul →
inferno	13–6	0.05	6%	1 Jul →
dust2	11–13	-0.01	9%	1 Jul →
nuke	9–7	0.01	17%	1 Jul →
dust2	13–7	-0.01	14%	1 Jul →
dust2	13–4	0.04	11%	30 Jun →
ancient	16–13	0.00	19%	30 Jun →
nuke	16–13	0.02	19%	30 Jun →
overpass	10–13	0.02	16%	29 Jun →
cache	13–5	-0.04	22%	29 Jun →
dust2	9–13	0.01	15%	29 Jun →
mirage	10–13	0.07	16%	29 Jun →
ancient	13–4	0.12	28%	29 Jun →
ancient	13–4	0.05	29%	28 Jun →
mirage	11–13	-0.01	14%	28 Jun →
ancient	13–6	-0.01	24%	28 Jun →
ancient	8–13	-0.06	19%	28 Jun →
anubis	13–5	0.07	15%	28 Jun →
nuke	9–13	0.12	15%	28 Jun →
dust2	13–11	0.04	21%	28 Jun →
dust2	13–7	-0.07	21%	27 Jun →
nuke	8–13	-0.06	8%	27 Jun →
mirage	6–13	0.02	25%	27 Jun →
ancient	13–11	0.05	20%	27 Jun →
nuke	16–14	-0.01	16%	27 Jun →
anubis	13–11	0.02	23%	27 Jun →
inferno	8–13	0.03	20%	24 Jun →
inferno	10–13	-0.02	12%	24 Jun →
dust2	5–13	-0.01	15%	23 Jun →
dust2	7–13	0.02	34%	23 Jun →
ancient	13–2	0.05	13%	23 Jun →
dust2	9–13	-0.00	23%	22 Jun →
nuke	5–13	-0.06	22%	22 Jun →
mirage	13–6	0.02	18%	22 Jun →
anubis	5–13	-0.00	6%	22 Jun →
anubis	12–16	0.00	18%	21 Jun →
mirage	13–6	0.00	11%	21 Jun →
mirage	15–15	-0.01	13%	20 Jun →
nuke	13–11	0.04	12%	20 Jun →
dust2	2–13	-0.05	17%	20 Jun →
dust2	13–9	0.10	25%	20 Jun →
inferno	2–9	-0.19	0%	19 Jun →
ancient	13–9	0.02	12%	19 Jun →
nuke	6–13	0.02	16%	19 Jun →
ancient	13–8	0.04	13%	19 Jun →

Show all 100 matchesShow fewer

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches

Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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